AI To Impact

PODCAST: AI for the Digital Enterprise

Episode 7: How GICs are powering AI enabled transformation

Listening time: 24 minutes

How GICs are powering AI enabled transformation

In this episode of the AI to Impact podcast, host Venkat Subramanian engages in a stimulating discussion with Sid Banerjee on his early corporate experience of driving growth and innovation at Global In-house Centers (GICs). They touch upon the role of GICs in driving the digital transformation agenda, the high visibility it brings to all functional areas of an organization, and the part it plays in bridging the gap between growth inefficiencies and cost management. Today the power of harnessing data is immense, and GICs are investing extensively in driving efficiencies through automation. The evolution of GICs with the all important charter of increasing adoption of AI powered decision making has led to a massive shift in the way enterprises are thinking about the role of GICs across the whole spectrum of industries. Tune in to listen to this insightful podcast!

This industry initially was, of course, everybody came to India and played a cost arbitrage game. And then finally they said, No, we are seeing some reasonably smart people, and can we do the value play. But lately, if you see, you know, from the transition to transformation, it’s all about innovation that we’re talking about. And therefore, a lot of Central excellence is coming up. We are getting certain global leaders being domiciled in these locations and these centers. And a lot of key agenda is being driven from these centers. So you know, that way, it’s been a massive, I would say, a paradigm shift in the way this is worked.

Venkat: Welcome to a brand new episode of the AI to impact podcast, and I’m your host – Venkat Subramanian. We started this podcast about a year ago, and it’s been a pretty interesting journey so far. We’ve had the opportunity to talk to several thought leaders, both from BRIDGEi2i and from the industry, and cover a whole range of topics around how enterprises are adopting AI and what it means for them in the context of digital transformation.

So, a little bit about myself, my name is Venkat Subramanian and I head marketing for BRIDGEi2i. Close to a 20-year career now in marketing. I started as an advertising, creative director, then moved on to marketing communications and then moved to marketing. So, over the last 15 years or so, I’ve been mostly in B2B marketing. The last five years have been at BRIDGEi2i, pretty much responsible for all aspects of marketing, brand development, demand generation pretty much the entire gamut. So pretty exciting journey with BRIDGEi2i and it’s been great to see how BRIDGEi2i has grown from strength to strength, the last few years. Today, I have another stalwart in this podcast, like we always tried to do with many of our other podcasts. I have Sid Banerjee here.

Now Sid and I go back a long way. We were colleagues at HP, almost, I would say 15 years back, and very interesting to cross paths with him here again, at BRIDGEi2i. He’s an advisor on BRIDGEi2i’s advisory board, and he’s also helping us steer, you know, the whole Europe business in the capacity as Europe Business Head. Today, I’ll be talking to him about something very interesting, based on his experience, so far in the industry. So Sid, you know, welcome to the show, welcome to this podcast, very excited to have you here.

Sid: Thank you, Venkat. Thank you. Okay, so Venkat, you’re basically making me go down three decades because that’s when my career started, and will be an arduous task, but I’ll try. Post my CA, I thought I would become an investment banker because that was fashionable, and I was lucky to have joined a few of these large IBs at that point of time.

Subsequently, I saw the rise and rise of the IT and then the ITDS industry consequent to which I also, you know, got into that space and that’s when I actually landed up at HP and had the good fortune of knowing you.

And then, you know, somewhere I combined this financial services and outsourcing industry experience to have set up Deutsche Bank’s offshoring outfit in India, which I then extended to IHS market as their CEO in India. And then finally, in Credit Suisse, again, where I held the global role, has been interesting, to say the least. And I think, as I keep telling people that, you know, I’m on my second or on my third innings, I think this new journey of getting to know, the digitization, and these AI ML analytics is even more interesting. And I am very lucky to again, you know, be on BRIDGEi2i’s advisory board, as you said, and see this journey unfold.

Venkat: Excellent. So I remember when I joined HP and you were part of the Shared Services Unit then and analytics was just, you know, it was gaining momentum, there was so much buzz around analytics. Everybody was, you know, trying to set up shop, trying to figure out, you know, what was this all about how to get value from it. So, from that time to today, it’s come a long way. Right? It’s become integral to business now. So, in the last so many years, since it’s sort of, you know, since it gained momentum in businesses and it became core, how do you see the evolution and how much of the analytics is actually being used today? And what are the changes you’ve seen in the last couple of decades?

Sid: Yeah, you know, Venkat, what I will do is I’ll give you a slightly different context here. Because once in 2018, I stepped out of my, you know, classical corporate journey, I, as you probably know, I also joined as an advisor with Deloitte. And that helped me, you know, go across industries and across companies, to, you know, spend time with the leaders. And one big realization was that this adoption of analytics or digitization, actually not just very strong industry to industry or company to company, it even varies depending on which function you belong to, which geographic location you’re based out of, and even on individual personas, right? So it’s very difficult to give a broad-brush response to this question to say there is a, you know, General learning curve, movement. But you know, what I’ve increasingly seen is that people have at least started to understand the power of data, there is a fair amount of appreciation of incredible insights that is possible to get or incredible actions that you can emanate from this. But many still think that this is not for them. I mean, I’m just talking more on the functional heads. And they still think that it’s the charter of the technology team to drive and hence become more an executor, as opposed to a thinker, or somebody who’s a thought leader in this space. So I’ve, you know, kind of seen that spectrum in this space.

Venkat: So Sid, I was just going through your LinkedIn profile. I know you from a long time, but you know, just for the sake of talking points, I just wanted to understand your career. So I went to your LinkedIn profile, and I must say, a pretty stellar career. I also noticed you spent a lot of time at GICs – building and driving growth for them. And at large enterprises,large companies. What was that experience like?

Sid: So you know, me for a long time, so I’ll let it pass. Otherwise, stellar is a heavy word. And I don’t want to be embarrassed. But I must say that I was very lucky to have seen this industry grow and really prosper. You know, it’s a bit of a right time, right place, and I really enjoyed that journey. So you know, this industry initially was a cost play, everybody came to India and played the cost arbitrage game. And then finally, they said, no, we are seeing some reasonably smart people, and can we do the value play? But lately, if you see, you know, from the transition to transformation, it’s all about the innovation that we’re talking about. And therefore, a lot of central excellence is coming up, we are getting certain global leaders being domiciled in these locations, and these centers, and a lot of key agenda is being driven from these centers. So you know, that way, it’s been a massive, I would say, a paradigm shift in the way this is worked. And lately, I’m also seeing a lot of, you know, analytics type Center of Excellence is coming up in these locations. And now that could be a bank, that could be an oil and gas company, that could be you know, CPG, but across the board, and again, both in BRIDGEi2i and in Deloitte conversations, I found that happens a lot, which is very, very welcoming. And when I talk to my old friends in this space, as well, I’m hearing them that their global counterparts are trying to realize that with the quant brain that you have in India, this is really something that they want to harness. So yes, it’s been almost 360-degree in terms of from where we started as a cost play to something that we are saying that the real cutting edge work will get out from here.

Venkat: Got it. So with this data revolution, you know, gaining so much momentum, you know, and everybody investing in analytics, and with ROI also becoming more and more tangible, how is the charter of GICs really changed? Because, you know, it seems like across industries, a lot of enterprises are setting up GICs across the world right. So how, how is this charter changed? What kind of value are they bringing to these enterprises?

Sid: So value is you know, originally was as I said, it was more like an offshore center in some of them thought okay, we have a nearshore now, and then offshore and nearshore together we’ll do stuff which is more transactional, which is more rule-based and then they started to say, okay, from that, can we move more to judgment-based, more to value-centric as you are alluding to. So that’s been there. But that’s also been there for more than ten years now. But recent trending has been, you know, to build some of these, so-called COEs,where there’s an RPA, right, COE, that, okay, we will adopt a blue prism, but in order to, you know, leverage the full power of that technology, that whole think tank will sit out of a location that could be in India, that could be in Budapest, you know, that kind of stuff. So that’s how I’m seeing, and in that, you know, a marketing would like to drive some of the new strategy, but there could be a analytics team sitting in India, which will partner with them to drive that new customer acquisition plan. So this is the sort of partnership that’s more coming up, which is, you know, more real-time, more dynamic, as opposed to a transactional activity, which is chucked over the wall and twenty-four hours later, you would see that work is done when they come back to office next morning. So I think that’s where the big shift is happening. I’m not saying that those transactional processing work is not happening. But a lot of automation is getting there, where I’m seeing this work is moving up the curve, from actually trying to drive that pure processing type work to more of strategic thinking work.

Venkat: Very interesting, because I know, that this has come a long way from the outsourcing wave to, you know, which is the cost play to more of knowledge process outsourcing, and then now we’re talking about more tighter integration of the business trying to, you know, drive some very specific business objectives. So, pretty interesting, you know, evolution, I would say, and so, just to build on that a little bit, while you’re, you know, the corporate functions or specific functions like marketing, sales, supply chain, while they’re looking at, obviously analytics to drive growth inefficiencies, and I’m sure they’re also trying to work with GICs for some of these. So how do GICs actually pick up some of these objectives and say, you know, I’m going to sign up for these objectives, let’s say in supply chain, or I’m going to help you, you know, drive better transformation in the marketing. How do GICs play a pivotal role in driving this agenda?

Sid: So Venkat, this will almost sound like a sales pitch, if I say how they should drive this, because this is the conversation I’m trying to have with many of them, especially in the last three-four months because traditionally, GICs are known to be executors and order takers.

Venkat: Right. Right.

Sid: And they have missed out on the opportunity of really harnessing the power of data that sits there. If you just look at GIC vis a vis even the head office in any other place, you would see that no other offices of any organization has the amount of visibility across function across businesses, as the GIC would have. But unfortunately, that sits in silos, and therefore the GIC never really brings all of that together, sees the holistic picture and plays it back to their think tanks or the strategic leadership team to be able to drive directionally these organizations, right. So I’m trying to, you know, help them see some of this and tell them that to do this you will obviously have to rely on technology, rely on analytics, rely on some of these trends, to be able to pick up these signals and play it back. But the power of harnessing that data is immense, and I think GICs can really have a meaningful seat at the table globally and can drive strategies or key agendas of large organizations here on.

Venkat: Yeah, and we are seeing this with some of our clients as well, right? I mean, we’re seeing how a lot of these were projects initially, but now how it’s almost a collaborative effort to drive some of these very important programs which have a central visibility in those organizations? So you’re absolutely right, I think that that’s where it’s heading. So you know, I’m going to use this phrase which we often hear in boardrooms saying you gotta eat your own dog food right. So, given that, you know, GICs are investing capabilities and trying to drive similar analytics and automation kind of, you know, objectives for the enterprises, how can they actually use this to become efficient themselves as a center?

Sid: No, Good point, good point. Eat your own cooking – quite a common phrase. In fact, in one of them, I remember, in my corporate career, I went to Poland, and we did this workshop where we were all supposed to do your own cooking. I had certainly avoided my own, knowing how interesting that would taste. But I did salad by the way.

Sid: So we’ll come back to your question. Clearly, there are two-three areas, right. One is this whole, you know, operation centers, when you run, you run large production shops. So the ability to get an early warning signal in seeing where the next big mess is going to happen, whether in terms of, you know, missing on the timeline, or actually having error in the report or not sending something on time… you could today, with the help of analytics, you can actually predict that, right? Because all these organizations have a very meticulous way of capturing their incidents, and the incidents are typically all the errors. But no one really goes back and, you know, analyzes them and proactively predicts where the next big fire is going to happen. But it’s very, very possible with the, you know, use of a nice Watchtower kind of tool. And I see that as an immediate use, you know, from these organizations. And that can actually drive a lot of actions, like, you know, it can tell them who to train, when they need to be trained, or whether there is a wrong profiling of resource, whether certain teams are overburdened, because the volume predicted is much lesser than what we’re really facing today. And therefore, you know, what sort of quality control should you have? How do you optimize those teams? So, all in all, I think it will improve their performance, it will right-size their teams, right train them, and clearly help in good cost management, because either you will have a situation where certain teams are carrying more people, and certain teams are getting less people, some getting more over skilled people, some carrying under profile people. So all of this balancing can very well happen if they start to use analytics, and this is just one example. But I think I see a lot of opportunity, you know, having run those shops, I can today see how much we can use this.

Venkat: Interesting that you touched upon cost management because, you know, that was sort of my next question. So, given, you know, these GICs are an investment and there are obviously a certain set of outcomes that, you know, these companies expect from the GICs, I’m sure cost management is one of those key metrics they focus on. And when it comes to KPI tracking, analytics has a huge role to play. And I’m sure while they are investing in analytics, programs and objectives, they’re also trying to use analytics to track, you know, from across management perspective. So what’s your take on this? How can analytics help run tighter ships and also drive better outcomes?

Sid: So very quickly, there are three steps I see. The purpose of this is always centralized standardization, so therefore, you know, you will get scale benefit. But then today with automation, you know, there is a clear adoption of RPA, there are opportunities seen in terms of becoming more efficient through, you know, some sort of introduction of even machine learning, and artificial intelligence, and so on, and so forth. And finally, you know, some of them, you know, little bit of unknown unknowns, like, you know, things like you make payment, but do you always make payment early, or sometimes do you make payment late? So both are a problem. If you pay early, then you’re losing on interest, if you pay late, then you’re paying a penalty. But, you know, we hardly track that as a metric, or odd, you know, reports, there’s so many reports that come out of this sort of centers, but nobody really knows who is reading the report, are they meeting the demands of the report, are you people still having a separate setup to generate those reports while we are independently churning out reports? So some of those information, if it can be captured, can also be very useful. So you know, they use it, as I see it in many folds.

Venkat: Okay. Okay. So, you know, I’ve been seeing this trend over the last maybe two or three years where, while large enterprises are setting up GIC’s and you know, having them run specific agendas, GICs themselves are also trying to partner with analytic service providers or, you know, AI consultancies to drive specific programs and initiatives. So how does this really fit into the corporate strategy, and how do they really find the balance between, you know, in sourcing some of these objectives and working with partners?

Sid: Good question, Venkat. And not the easiest to respond to, because people are grappling with them.

Venkat: I’m sure.

Sid: Yeah. But you know, what we have seen. And again, I’ll use my personal experience to see when I was trying to set this up in Credit Suisse, we realized that initially every organization’s view is that if it’s mission-critical, if it’s domain heavy, then it should sit inside. But if it is more technology-centric, then you should probably send it outside because, you know, you need to get the best of the breed. But my realization is that the whole ecosystem of high quality talent in this space is very, very difficult to build in our organization where banking is their core, or where manufacturing is their core, or where, you know, advertising is their core. So you know, to get such talent and get them to constantly upgrade/update themselves and add value is going to be far more challenging, as against, you know, trying to give it to a good partner with whom you have to have a long term relationship, but use them as an extended arm, and try to do some of these cutting edge stuff, maybe outside their office rather than inside, but more using it like an extension.

Venkat: Got it. That’s it; it’s amazing to see how these models keep on evolving. Some are obviously very conscious, you know, shift in strategy, and some are probably more organic in nature, because, you know, that’s the need of the hour, that’s probably the best way to extract value out of these models. So it’s, it’s, you know, it’s been a fascinating window into the world of gic. And its evolution. And obviously, you having spent so much time working with these companies and building and driving these centers for them. So it’s been fascinating, Sid and you know, just getting to understand that world and how it works and where it’s all going. I think it’s been a really rich and enriching conversation, to say the least. So slightly shifting gears to a more personal side, I’ve been hearing that you’re very passionate about theater, and you’ve been, you know, participating in some plays, obviously, before the whole COVID situation happened. So how is that shaping up? You know, I would love to understand, you know, that side of your life as well, to a little bit.

Sid: See Venkat after three decades of corporate world, acting comes naturally. So I thought, why not get into professionalism. And today, all I can tell you is that I have three plays ready but have no audience, and I don’t know when the audience will come back. But the first play that I started and I had done nine shows of it, they were luckily pretty much all housefull, nothing to do with me, but some good marketing and the team and I really enjoyed it, you know, to walk into a live audience is a different experience altogether, and really enjoying it. And thanks for asking, Venkat.

Venkat: Excellent Sid, thanks for making time for this interaction. I am sure we will attack more topics in the future. And I’d love to have more conversations about a lot, many more topics with you. But for this one, I think it’s going to be a wrap. Thank you again, and catch up soon.

Sid: Bye. Take care, Venkat.

Venkat: Thank you.

Sid: Pleasure.

Venkat: Thank you so much for listening to this episode of AI to Impact podcast. We are very enriching conversation with Sid today. And I had the good fortune of picking his brain to understand the evolution of the GIC business, how analytics is driving growth and GICs, and making them more efficient as a center. We also got to talk a lot about the future of GICs and how they can actually drive a lot of impact for the enterprise itself. If you find this conversation interesting, please subscribe to our podcast and feel free to share in the info. Thank you. Stay home and stay safe.

The upswing in AI adoption and the impact of Digital initiatives in enterprise transformation have reached staggering heights, but there is still a lot of skepticism around the value realization of AI. BRIDGEi2i, a transformation partner to several large enterprises, has been spearheading an enterprise-wide movement on “Making AI Real.” In this series, we bring together reputed thought leaders, practitioners, and influencers of the industry as they discuss trends, predictions, and best practices on extracting tangible value from AI to embark on transformational journeys.

Meet the Speaker

Sid Banerjee Speaker

Sid Banerjee – Advisor, BRIDGEi2i

Sid Banerjee is a member of the Advisory Board and plays a key role in mentoring European Business Development at BRIDGEi2i.

He has over three decades of experience in investment banking, technology, and the offshoring industry. He currently serves on multiple boards and is vested in several startups. A qualified Chartered Accountant with a deep understanding of the banking infrastructure and its functioning in finance, technology, and mid-office operational areas, he has previously held many senior positions namely MD, Credit Suisse Group; MD, Deutsche Bank Group; CEO, IHS Markit, and VP, HP Global.

Venkat Subramanian Speaker

Venkat Subramanian – CMO, BRIDGEi2i

Venkat heads Marketing for BRIDGEi2i. He has over 20 years of experience in Marketing, Marketing Communications, and Creative Services. Prior to BRIDGEi2i, Venkat has held leadership positions at companies like RR Donnelley, HP, Wipro and GEP in a variety of roles across marketing communications, marketing ops and marketing with accomplishments that include building global footprint for brands, setting up and managing large offshore Marcom services business, and developing brand and demand generation strategies. Venkat is a Mechanical Engineer with an Executive MBA from IIM, Bangalore.

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